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arXiv 2022年

作者： Huo, Cuiying He, Dongxiao Li, Yawen Jin, Di Dang, Jianwu Zhang, Weixiong Pedrycz, Witold Wu, Lingfei College of Intelligence and Computing Tianjin University Tianjin300350 China School of Economics and Management Beijing University of Posts and Telecommunications Beijing100876 China Dept of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Anytime.AI ArmonkNY10504 United States

Heterogeneous graph neural network (HGNN) is a popular technique for modeling and analyzing heterogeneous graphs. Most existing HGNN-based approaches are supervised or semi-supervised learning methods requiring graphs to be annotated, which is costly and time-consuming. Self-supervised contrastive learning has been proposed to address the problem of requiring annotated data by mining intrinsic properties in the given data. However, the existing contrastive learning methods are not suitable for heterogeneous graphs because they construct contrastive views only based on data perturbation or pre-defined structural properties (e.g., meta-path) in graph data while ignoring noises in node attributes and graph topologies. We develop the first novel and robust heterogeneous graph contrastive learning approach, namely HGCL, which introduces two views on respective guidances of node attributes and graph topologies and integrates and enhances them by a reciprocally contrastive mechanism to better model heterogeneous graphs. In this new approach, we adopt distinct but most suitable attribute and topology fusion mechanisms in the two views, which are conducive to mining relevant information in attributes and topologies separately. We further use both attribute similarity and topological correlation to construct high-quality contrastive samples. Extensive experiments on four large real-world heterogeneous graphs demonstrate the superiority and robustness of HGCL over several state-of-the-art methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Graph neural networks

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A bilateral game approach for task outsourcing in multi-access edge computing

arXiv

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arXiv 2020年

作者： Xiao, Zheng He, Dan Chen, Yu Chronopoulos, Anthony Theodore Dustdar, Schahram Du, Jiayi College of Computer Science and Electronic Engineering Hunan University Hunan410082 China Department of Computer Science University of Texas San AntonioTX78249 United States Dept Computer Engineering Informatics University of Patras Rio26500 Greece Distributed Systems Group Vienna University of Technology Vienna Austria

Multi-access edge computing (MEC) is a promising architecture to provide low-latency applications for future Internet of Things (IoT)-based network systems. Together with the increasing scholarly attention on task offloading, the problem of edge servers’ resource allocation has been widely studied. Most of previous works focus on a single edge server (ES) serving multiple terminal entities (TEs), which restricts their access to sufficient resources. In this paper, we consider a MEC resource transaction market with multiple ESs and multiple TEs, which are interdependent and mutually influence each other. However, this many-to-many interaction requires resolving several problems, including task allocation, TEs’ selection on ESs and conflicting interests of both parties. Game theory can be used as an effective tool to realize the interests of two or more conflicting individuals in the trading market. Therefore, we propose a bilateral game framework among multiple ESs and multiple TEs by modeling the task outsourcing problem as two noncooperative games: the supplier and customer side games. In the first game, the supply function bidding mechanism is employed to model the ESs’ profit maximization problem. The ESs submit their bids to the scheduler, where the computing service price is computed and sent to the TEs. While in the second game, TEs determine the optimal demand profiles according to ESs’ bids to maximize their payoff. The existence and uniqueness of the Nash equilibrium in the aforementioned games are proved. A distributed task outsourcing algorithm (DTOA) is designed to determine the equilibrium. Simulation results have demonstrated the superior performance of DTOA in increasing the ESs’ profit and TEs’ payoff, as well as flattening the peak and off-peak load. Copyright © 2020, The Authors. All rights reserved.

关键词： Game theory

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Virtual Cluster Head Based PSO and Fuzzy Logic Approach for WSN to Extend Network Lifetime

Virtual Cluster Head Based PSO and Fuzzy Logic Approach for ...

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2020 International Conference on Computing and Information technology, ICCIT 2020

作者： Manikandan, V. Mavaluru, DInesh Gobinathan, K. Rajanarayanan, S. Jenifer, M. Rohini, R. Lebanese French University Department of Computer Networking Erbil Kurdistan Region Iraq Saudi Electronic University College of Computing and Informatics Department of Information Technology Saudi Arabia Gnanamani Collge of Technology Department of CSE Namakkal India Arba Minch University Dept. of Business Administration and Information System Ethiopia Arba Minch University Arba Minch Institute of Technology Faculty of Computing and Software Engineering Ethiopia Vivekanandha College of Engineering for Women Department of CSE Namakkal India

ISBN: (纸本)9781728126807

In recent times, Wireless Sensor Networks (WSNs) are broadly utilized in targeted monitoring applications. Traditional target coverage techniques usually consider that environment is known completely and every target is covered by single sensor. However those algorithms are inflexible when the sensor is about to die, that is, lack of energy and therefore target has to be covered with more than a sensor which is termed as n coverage crisis. In general, n coverage problem is energy and time consuming process, as well sensor organization is needed all the time. To resolve this crisis, this work anticipates a n coverage model with VCH-PSO (Virtual Cluster Head based Particle Swarm Optimization and EFLM (Energy management based Fuzzy logic Model) to enlarge the lifetime of WSN. During the search of optimal area coverage, diverse factors like node position, energy consumption, and coverage range of sensors are considered significantly. Simulation was carried out in MATLAB environment and compared with prevailing techniques. The proposed model shows better trade off in terms of network lifetime and time needed for switching between various coverage regions. © 2020 IEEE.

关键词： Fuzzy logic

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Assessing responsible innovation training

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Journal of Responsible technology 2023年 16卷

作者： Stahl, Bernd Carsten Aicardi, Christine Brooks, Laurence Craigon, Peter J. Cunden, Mayen Burton, Saheli Datta Heaver, Martin De Saille, Stevienna De Dolby, Serena Dowthwaite, Liz Eke, Damian Hughes, Stephen Keene, Paul Kuh, Vivienne Portillo, Virginia Shanley, Danielle Smallman, Melanie Smith, Michael Stilgoe, Jack Ulnicane, Inga Wagner, Christian Webb, Helena School of Computer Science University of Nottingham United Kingdom Dept. of Informatics and School of Biomedical Engineering & Imaging Sciences King's College London United Kingdom Information School University of Sheffield Sheffield United Kingdom Horizon Digital Economy Research School of Computer Science University of Nottingham United Kingdom Independent Researcher Dept of Science and Technology Studies University College London United Kingdom ORBIT RRI limited Leicester United Kingdom Dept of Sociological Studies University of Sheffield Sheffield United Kingdom Centre for Computing and Social Responsibility De Montfort University Leicester United Kingdom School of Chemistry University of Bristol United Kingdom Department of Philosophy Faculty of Arts and Social Sciences Maastricht University Netherlands Biodiversity and Conservation Science Department of Biodiversity Conservation and Attractions Wildlife Research Centre Western Australia De Montfort University United Kingdom Lab for Uncertainty in Data and Decision Making (LUCID) School of Computer Science University of Nottingham United Kingdom

There is broad agreement that one important aspect of responsible innovation (RI) is to provide training on its principles and practices to current and future researchers and innovators, notably including doctoral students. Much less agreement can be observed concerning the question of what this training should consist of, how it should be delivered and how it could be assessed. The increasing institutional embedding of RI leads to calls for the alignment of RI training with training in other subjects. One can therefore observe a push towards the official assessment of RI training, for example in the recent call for proposals for centres for doctoral training by UK Research and Innovation. This editorial article takes its point of departure from the recognition that the RI community will need to react to the call for assessment of RI training. It provides an overview of the background and open questions around RI training and assessment as a background of examples of RI training assessment at doctoral level. There is unlikely to be one right way of assessing RI training across institutions and disciplines, but we expect that the examples provided in this article can help RI scholars and practitioners orient their training and its assessment in ways that are academically viable as well as supportive of the overall aims of RI. © 2023

关键词： Assessment Doctoral training Education Responsible innovation

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A Survey on the E-learning platforms used during COVID-19 11

A Survey on the E-learning platforms used during COVID-19

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11th Annual IEEE Information technology, Electronics and Mobile Communication Conference, IEMCON 2020

作者： Wang, Xianping Chen, Weiru Qiu, Hao Eldurssi, Awad Xie, Fei Shen, Jiayue Purdue University Northwest Dept of Computer Information Science and Graphics HammondIN46323 United States Old Dominion University Dept of Information Technology and Decision Sciences NorfolkVA23529 United States Fort Valley State University Dept of Engineering Technology Fort ValleyGA31030 United States Fort Valley State University Dept of Engineering Technology Fort ValleyGA31030 United States School of Informatics Computing and Cyber Systems Northern Arizona University FlagstaffAR86011 United States College of Engineering Suny Polytechnic Institute UticaNY13502 United States

ISBN: (纸本)9781728184166

E-learning is globalized in a short period of time due to the physical distancing requirement for curbing the spread of COVID-19. There are two major challenges imposed by the migration from face-To-face learning to E-learning: live lecturing and lab sessions. In this survey, we studied the E-learning platforms used in the COVID-19 pandemic: learning management systems or course management systems, tools for live-lecturing and tools for lab sessions. We found that this migration is quite smooth with contemporary technologies and the Internet. Prescriptive suggestions are also provided for this migration. For the future trend of education, it is expected that E-learning will become a preferable education and learning style in the future, especially for self-study and life-long learning. © 2020 IEEE.

关键词： COVID-19

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Unbounded regions of high-order Voronoi diagrams of lines and segments in higher dimensions 30

Unbounded regions of high-order Voronoi diagrams of lines an...

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30th International Symposium on Algorithms and Computation, ISAAC 2019

作者： Barequet, Gill Papadopoulou, Evanthia Suderland, Martin Dept. of Computer Science Technion - Israel Inst. of Technology Haifa3200003 Israel Faculty of Informatics Università Della Svizzera Italiana Lugano Switzerland

ISBN: (纸本)9783959771306

We study the behavior at infinity of the farthest and the higher-order Voronoi diagram of n line segments or lines in a d-dimensional Euclidean space. The unbounded parts of these diagrams can be encoded by a Gaussian map on the sphere of directions Sd−1. We show that the combinatorial complexity of the Gaussian map for the order-k Voronoi diagram of n line segments or lines is O(min{k, n−k}nd−1), which is tight for n−k = O(1). All the d-dimensional cells of the farthest Voronoi diagram are unbounded, its (d−1)-skeleton is connected, and it does not have tunnels. A d-cell of the Voronoi diagram is called a tunnel if the set of its unbounded directions, represented as points on its Gaussian map, is not connected. In a three-dimensional space, the farthest Voronoi diagram of lines has exactly n2−n three-dimensional cells, when n ≥ 2. The Gaussian map of the farthest Voronoi diagram of line segments or lines can be constructed in O(nd−1α(n)) time, while if d = 3, the time drops to worst-case optimal O(n2). © Gill Barequet, Evanthia Papadopoulou, and Martin Suderland;licensed under Creative Commons License CC-BY

关键词： Gaussian distribution

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Computational Approaches to Explainable Artificial Intelligence: Advances Intheory, Applications and Trends

SSRN

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SSRN 2023年

作者： Górriz, Juan Manuel Álvarez-Illán, I. Álvarez-Marquina, A. Arco, J.E. Atzmueller, M. Ballarini, F. Barakova, E. Bologna, G. Bonomini, P. Castellanos-Dominguez, G. Castillo-Barnes, D. Cho, S.B. Contreras, R. Cuadra, J.M. Domínguez, E. Domínguez-Mateos, F. Duro, R.J. Elizondo, D. Fernández-Caballero, A. Fernandez-Jover, E. Formoso, M.A. Gallego-Molina, N.J. Gamazo, J. García González, J. Garcia-Rodriguez, J. Garre, C. Garrigós, J. Gómez-Rodellar, A. Gómez-Vilda, P. Graña, M. Guerrero-Rodriguez, B. Hendrikse, S.C.F. Jimenez-Mesa, C. Jodra-Chuan, M. Julian, V. Kotz, G. Kutt, K. Leming, M. de Lope, J. Macas, B. Marrero-Aguiar, V. Martinez, J.J. Martinez-Murcia, F.J. Martínez-Tomás, R. Mekyska, J. Nalepa, G.J. Novais, P. Orellana, D. Ortiz, A. Palacios-Alonso, D. Palma, J. Pereira, A. Pinacho-Davidson, P. Pinninghoff, M.A. Ponticorvo, M. Psarrou, A. Ramírez, J. Rincón, M. Rodellar-Biarge, V. Rodríguez-Rodríguez, I. Roelofsma, P.H.M.P. Santos, J. Salas-Gonzalez, D. Salcedo-Lagos, P. Segovia, F. Shoeibi, A. Silva, M. Simic, D. Suckling, J. Treur, J. Tsanas, A. Varela, R. Wang, S.H. Wang, W. Zhang, Y.D. Zhu, H. Zhu, Z. Ferrández-Vicente, J.M. SiPBA at Data Science and Computational Intelligence Institute University of Granada Granada Spain University of Granada Granada Spain Dept. of Psychiatry University of Cambridge Cambridge United Kingdom Dept. of Communications Engineering University of Malaga Malaga Spain School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Semantic Information Systems Group Osnabrück University Osnabrück Germany Osnabrück Germany Dept. of Electronics Computer Technology and Projects Universidad Politécnica de Cartagena Cartagena Spain Universitat Politècnica de València València Spain Institute of Applied Computer Science Jagiellonian University Kraków Poland Dept. of Information and Communication Engineering University of Murcia Murcia Spain Dept. of Computer Science and Information Technologies University of A Coruña A Coruña Spain Dept. of Computer Science University of Oviedo Oviedo Spain Buenos Aires Argentina Buenos Aires Argentina Eindhoven University of Technology Eindhoven5612 AZ Netherlands Dept. of Computer Science University of Malaga Malaga Spain De Montfort University Leicester United Kingdom Dept. of Computer Science Faculty of Engineering Universidad de Concepción Concepción Chile Neurocognition and Emotion Research Unit Albacete Research Institute of Informatics University of Castilla-La Mancha Albacete Spain Dept. of Educational Informatics Universidad de Concepción Concepción Chile Madrid Spain Dept. of Humanistic Studies University of Naples Federico II Napoli Italy Escuela Técnica Superior de Ingeniería Informática Universidad Rey Juan Carlos Campus de Móstoles Móstoles Madrid28933 Spain Neuromorphic Speech Processing Lab Center for Biomedical Technology Universidad Politécnica de Madrid Campus de Montegancedo Pozuelo de Alarcón Madrid28223 Spain Biomedical Research Networking Center in Mental Health Instituto de Salud Carlos III Madrid28016 Spain Usher Institute Faculty o

Groundbreaking advances in theoretical and applied Artificial Intelligence (AI). DL algorithms are groundedin non-linear and complex artificial neural systems that progressively extract higher-level features from *** is frequently compared with human-level performance in real-world tasks, such as clinical diagnostics. Itis also a turning point in solving otherwise intractable problems in the design of virtual agents or robotics;orin providing novel insight into disease progress in genomics and Neuroimaging (NI), understanding humanbrain function, the automation of industrial processes based on computer vision, and so on. In this paper, themost relevant advances from the last few years in AI and several applications to neuroscience, neuroimaging,computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-ofthe-art in AI methods, models and applications within a collection of works presented at the 9th InternationalConference on the Interplay between Natural and Artificial Computation (IWINAC). The works presentedin this paper are excellent examples of new scientific discoveries made in laboratories that are successfullytransferred to real-life applications. © 2023, The Authors. All rights reserved.

关键词： Neuroimaging

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Correlation Analysis with Experimental Procedures and Peak Structures in Xps Spectral Round-Robin Tests on Mno Powder Sample

SSRN

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SSRN 2022年

作者： Murakami, Ryo Harada, Yoshitomo Sonobayashi, Yutaka Oji, Hiroshi Makino, Hisao Tanaka, Hiromi Taguchi, Hideyuki Sakamoto, Takanori Morita, Haruka Wakamori, Akihiko Kibe, Naoko Nishida, Shinsuke Nagata, Kenji Shinotsuka, Hiroshi Shouno, Hayaru Yoshikawa, Hideki The University of Electro-Communications Graduate School of Informatics and Engineering Chofu182-8585 Japan National Institute for Materials Science Research and Services Division of Materials Data and Integrated System Ibaraki Tsukuba305-0044 Japan Kyoto University Department of Materials Science and Engineering Kyoto606-8501 Japan Nagoya University Synchrotron radiation Research center Nagoya464-8603 Japan Kochi University of Technology School of Systems Engineering Japan National Institute of Technology Yonago College Department of Electrical and Computer Engineering Japan Nihon Parkerizing Co. Ltd Central Research Laboratories Kanagawa 254-0012 Japan JX Nippon Mining & Metals Corporation Technology Development Center Japan Melco Semiconductor Engineering Corporation Chemical Analysis & Evaluation Engineering Dept. Fukuoka Japan Kobelco Welding TechnoSolutions Co. Technical Solution Dept. Ltd Kanagawa 251-8551 Japan Furukawa Electric Co. Ltd Analysis Technology Center Sustainable Technology Laboratorie Kanagawa 220-0073 Japan

Spectral measurements provide valuable information on the electronic states and crystal structures of materials. In particular, X-ray photoelectron spectroscopy (XPS) can facilitate analysis of the chemical bond state of material surfaces. In the analysis of XPS spectra, the spectrum to be measured is typically compared to a reference spectrum measured on a known single-phase sample. Therefore, establishing a reference spectral database is imperative. In this study, round-robin tests of XPS spectra are performed with the aim of obtaining recommended XPS reference spectra and experimental procedures, including preprocessing. Determining the variations in peak structures between instrument- and sample-derived spectral shapes, and quantitatively discussing them in round-robin tests of XPS spectra are challenging. Therefore, an analysis method that automatically determines the above mentioned variations and extracts the samplederived common spectral structures is developed. This study presents a new approach to the quantitative analysis of round-robin tests of XPS spectra. The required common © 2022, The Authors. All rights reserved.

关键词： X ray photoelectron spectroscopy

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An Automated Biometric Identification System Using CNN-Based Palm Vein Recognition

An Automated Biometric Identification System Using CNN-Based...

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International Conference on Advanced Robotics and Intelligent Systems (ARIS)

作者： Sin-Ye Jhong Po-Yen Tseng Natnuntnita Siriphockpirom Chih-Hsien Hsia Ming-Shih Huang Kai-Lung Hua Yung-Yao Chen Dept. of Engineering Science National Cheng Kung University Tainan Taiwan Inst. of Automation Technology National Taipei University of Technology Taipei Taiwan Dept. of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan Dept. of Computer Science and Information Engineering National Ilan University Ilan Taiwan AI Fab Inc. Taipei Taiwan Dept. of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (数字)9781728198231

ISBN: (纸本)9781728198248

Recently, automated biometric identification system (ABIS) has wide applications involving automatic identification and data capture (AIDC), which includes automatic security checking, verifying personal identity to prevent information disclosure or identity fraud, and so on. With the advancement of biotechnology, identification systems based on biometrics have emerged in the market. These systems require high accuracy and ease of use. Palm vein identification is a type of biometric that identifies palm vein features. Compared with other features, palm vein recognition provides accurate results and has received considerable attention. We developed a novel high-performance and noncontact palm vein recognition system by using high-performance adaptive background filtering to obtain palm vein images of the region of interest. We then used a modified convolutional neural network to determine the best recognition model through training and testing. Finally, the developed system was implemented on the low-level embedded Raspberry Pi platform with cloud computing technology. The results showed that the system can achieve an accuracy of 96.54%.

关键词： Veins Feature extraction Convolution Cameras Electronic mail Filtering Convolutional neural networks

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Application of explainable artificial intelligence in medical health: A systematic review of interpretability methods

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informatics in Medicine Unlocked 2023年 40卷

作者： Shahab S Band Atefeh Yarahmadi Chung-Chian Hsu Meghdad Biyari Mehdi Sookhak Rasoul Ameri Iman Dehzangi Anthony Theodore Chronopoulos Huey-Wen Liang Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Taiwan Department of Information Management National Yunlin University of Science and Technology Taiwan Department of Computer Science Texas A&M University Corpus Christi Tx USA Department of Computer Science Rutgers University NJ USA Department of Computer Science University of Texas San Antonio TX 78249 USA Dept of Computer Engineering & Informatics University of Patras Greece Department of Physical Medicine and Rehabilitation National Taiwan University (NTU) College of Medicine Taipei Taiwan

This paper investigates the applications of explainable AI (XAI) in healthcare, which aims to provide transparency, fairness, accuracy, generality, and comprehensibility to the results obtained from AI and ML algorithms in decision-making systems. The black box nature of AI and ML systems has remained a challenge in healthcare, and interpretable AI and ML techniques can potentially address this issue. Here we critically review previous studies related to the interpretability of ML and AI methods in medical systems. Descriptions of various types of XAI methods such as layer-wise relevance propagation (LRP), Uniform Manifold Approximation and Projection (UMAP), Local Interpretable Model-agnostic Explanations (LIME), SHapley Additive exPlanations (SHAP), ANCHOR, contextual importance and utility (CIU), Training calibration-based explainers (TraCE), Gradient-weighted Class Activation Mapping (Grad-CAM), t-distributed Stochastic Neighbor Embedding (t-SNE), NeuroXAI, Explainable Cumulative Fuzzy Class Membership Criterion (X-CFCMC) along with the diseases which can be explained through these methods are provided throughout the paper. The paper also discusses how AI and ML technologies can transform healthcare services. The usability and reliability of the presented methods are summarized, including studies on the usability and reliability of XGBoost for mediastinal cysts and tumors, a 3D brain tumor segmentation network, and the TraCE method for medical image analysis. Overall, this paper aims to contribute to the growing field of XAI in healthcare and provide insights for researchers, practitioners, and decision-makers in the healthcare industry. Finally, we discuss the performance of XAI methods applied in medical health care systems. It is also needed to mention that a brief implemented method is provided in the methodology section.

关键词： Explainable artificial intelligence (XAI) Interpretability Health ML Methods Review

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